Registration of preoperative 3D data to 2D intraoperative fluoroscopy data has been widely proposed for a number of clinical applications. Systems for radiosurgery and neurosurgery are in widespread clinical use. These systems allow overlay of preoperative data onto interventional images or allow additional information from a preoperative Computerised Tomography (CT) scan (e.g. a radiotherapy plan) to be accurately aligned to the patient.
In more detail, prior to an operation a patient is typically subjected to a CT scan of the body area where the surgery will take place. This results in a three-dimensional image of the scanned body area. However, during surgery real time 2D fluoroscopy images are obtained of the same area, using for example a C-arm type fluoroscopy machine. However, a 2D fluoroscopy image may be insufficient to allow a surgeon to determine the precise position within the body of surgical instruments or surgical implants, particularly during catheter based MIS procedures. For example, during stent-graft repair of aortic aneurysms, precise stent placement is essential.
In order to address the drawbacks of the 2D images, it is known to augment the 2D real time image with the 3D pre-obtained image, obtained, for example from a CT scan. The problem then arises of ensuring accurate registration of the 3D image with the 2D image i.e. ensuring that the 2D image is aligned with the correct parts of the 3D image. FIG. 1 illustrates that CT position and orientation is defined by six rigid body parameters, being three translations X, Y, and Z, and three rotations θx, θy, and θz. These can be divided into parameters which define movements parallel to the plane of the fluoroscopy image (in plane parameters θx, Y, and Z), and parameters which define movements a component of which is normal to the fluoroscopy plane (out-of-plane parameters θy, and θz, and X). The registration problem is then one of how to manipulate these parameters such that the 3D data volume becomes aligned with the 2D image such that the surgeon can have some confidence in the registration achieved.
Various registration techniques are known in the art. Specifically, in Penney et at “An Image-Guided Surgery System to Aid Endovascular Treatment of Complex Aortic Aneurysms: Description and Initial Clinical Experience”, IPCAI 2011, LNCS 6689, pp. 13-24 the present inventors describe an intensity based registration technique which requires a starting position to be chosen by relying on visual inspection and identification of a vertebra in the fluoroscopy image. FIGS. 3(a) to (c) illustrate the procedure, where from an initial position (FIG. 3(a)) a region of interest is drawn (FIG. 3(b)) using a GUI, and the chosen 3D CT vertebra surface is then manually translated over the fluoroscopy vertebra (FIG. 3(c)).
Another technique is to use fiducial markers. Fiducial markers are frequently used as reference points to facilitate registration between an intraoperative image and a patient during surgery. The markers need to be attached prior to the pre-operative 3D imaging and then remain in place until surgery. This can be problematic if there is a large time period between imaging and surgery. In addition, the most accurate markers are bone implanted, which require an additional surgical procedure for their insertion. As such, fiducial markers are only usually used when absolutely necessary for the registration process, due to the significant additional costs and necessity of an additional surgical procedure. However, the use of fiducial markers can lead to good accuracy, and hence a system that provided the benefits of such markers but without the associated problems would be beneficial.